GABA-mediated inhibition of human CD4+ T cell functions is enhanced by insulin but impaired by high glucose levels

Summary Background γ-aminobutyric acid (GABA), known as the main inhibitory neurotransmitter in the brain, exerts immunomodulatory functions by interaction with immune cells, including T cells. Metabolic programs of T cells are closely linked to their effector functions including proliferation, differentiation, and cytokine production. The physiological molecules glucose and insulin may provide environmental cues and guidance, but whether they coordinate to regulate GABA-mediated T cell immunomodulation is still being examined. Methods CD4+ T cells that were isolated from blood samples from healthy individuals and from patients with type 1 diabetes (T1D) were activated in vitro. We carried out metabolic assays, multiple proximity extension assay (PEA), ELISA, qPCR, immunoblotting, immunofluorescence staining, flow cytometry analysis, MS-based proteomics, as well as electrophysiology and live-cell Ca2+ imaging. Findings We demonstrate that GABA-mediated reduction of metabolic activity and the release of inflammatory proteins, including IFNγ and IL-10, were abolished in human CD4+ T cells from healthy individuals and patients with T1D when the glucose concentration was elevated above levels typically observed in healthy people. Insulin increased GABAA receptor-subunit ρ2 expression, enhanced the GABAA receptors-mediated currents and Ca2+ influx. GABA decreased, whereas insulin sustained, hexokinase activity and glycolysis in a glucose concentration-dependent manner. Interpretation These findings support that metabolic factors, such as glucose and insulin, influence the GABA-mediated immunomodulation of human primary T cells effector functions. Funding The Swedish Children’s Diabetes Foundation, The Swedish Diabetes Foundation, The 10.13039/501100004359Swedish Research Council 2018-02952, EXODIAB, The Ernfors Foundation, The Thurings Foundation and the Science for Life Laboratory.


Introduction
Human T cells are a crucial component of the adaptive immune response and provide essential immune protection throughout life.Upon antigen stimulation, naïve T cells undergo clonal expansion and further differentiate into effector cells.During this process, metabolic reprogramming of T cells occurs and is intricately linked to their effector functions. 1][10] The GABA concentration in the plasma of healthy individuals is around 500 nM and increases somewhat in patients with type 1 diabetes (T1D) or major depression. 10,11In contrast, the GABA content in islets from patients with T1D is decreased relative to healthy individuals. 12Glucose is the primary source of energy for activated T cells but, is also utilised for synthesising biomolecules to support the rapid proliferation and differentiation of the cells. 13,14At the time of activation, glucose is mainly transported by glucose transporters that equilibrate glucose concentration across the cell membrane. 3The blood glucose concentration varies under physiological and pathophysiological conditions.The typical values for fasting blood glucose concentration in healthy individuals range between 3.9 mM and 5.6 mM glucose.Atypical, pathophysiological glucose levels are observed in diabetesrelated hypoglycaemia (<3 mM) or hyperglycaemia (>11 mM). 15In human clinical trials, GABA treatment has been shown to be beneficial for glycemic control in patients with T1D. 16,17Insulin, a hormone mainly associated with glucose homeostasis, 15 also influences T cell function by modulating their metabolism. 18We and others have previously demonstrated that GABA signalling regulates hormone secretion in human islets. 12,19,20However, how the metabolic factors glucose and insulin orchestrate and regulate GABA immunomodulation of T cell functions is still being uncovered.
In the present study, we observe that, in human CD4 + T cells, increasing the glucose concentration above typical physiological levels attenuates GABA-mediated inhibition of metabolic activity and release of inflammatory proteins, including IFNγ and IL-10.Furthermore, insulin augments GABA A receptor (GABA A R)-mediated currents and Ca 2+ influx in a manner that is dependent on the glucose concentration.Finally, we show that GABA, insulin and glucose differentially modulate glycolysis in activated CD4 + T cells.These results identify glucose and insulin as regulators of GABA immunomodulation impacting human CD4 + T cell effector functions.

Study individuals and collection of samples Ethics
Human blood buffy coats and blood samples were obtained from Uppsala University Hospital (Uppsala Akademiska Sjukhuset) following a protocol approved by the Regional Research Ethical Committee (EPN, https://etikprovningsmyndigheten.se) in Uppsala, Sweden (Dnr 2013/347 and Dnr 2014/485).All donors were

Research in context
Evidence before this study Activation of T lymphocytes is important in fighting various pathogens and cancer, but can also cause problems if erroneously activated such as in autoimmune diseases like type 1 diabetes.Within the body, physiological molecules provide environmental cues and guide the development of T cells.That neurotransmitters can affect immune cells has become apparent within the last decade.Immune cells can encounter neurotransmitters in the brain but also in lymph nodes, in blood and in the pancreatic islets.We and others have shown that the main inhibitory neurotransmitter γ-aminobutyric acid (GABA) can regulate proliferation and release of inflammatory proteins from T cells.In neurons, insulin regulates GABA signalling whereas in pancreatic islets, GABA affects insulin secretion.Antibodies against the glutamic acid decarboxylase, the enzyme synthesising GABA, are detected in type 1 diabetes while glucose concentration in blood is elevated and insulin levels are abnormal in both forms of diabetes (type 1 and 2).Therefore, we investigated how GABA, glucose and insulin modulate T cells immunomodulation.

Added value of this study
In this study we demonstrate that the physiological molecules GABA, glucose and insulin all shift the response of T cells.GABA normally puts a brake on T cells proliferation and secretion of inflammatory proteins by activating GABA A receptors channels, enhancing the intracellular Ca 2+ concentration by influx through CRAC channels and by reducing hexokinase activity but, interestingly, in a glucosedependent manner.Insulin, in turn, reinforces the GABAbrake on T cells.We elucidate the mechanism of how the GABA-brake comes about and have identified glucose and insulin as physiological molecules that can affect its effectiveness.We reveal that the main obstacle for effective GABA inhibition of T cells functions is high glucose concentration.The ion channels and an intracellular enzyme that participate in the GABA-brake may provide specific pharmaceutical targets.In addition, the results demonstrate that decreasing glucose levels reduces T cells-driven inflammation.

Implications of all the available evidence
Prior work has shown that GABA is an important modulator of T cells immune function in health and diabetes.The evidence indicates GABA serving as a homeostatic molecule in the immune system.Nevertheless, at glucose concentrations that may be observed in diabetes, the inhibition normally provided by GABA is overrun and T cells-driven inflammation prevails.The study suggests the importance of decreasing the glucose concentration to maintain the suppressive effect of GABA on inflammation.
voluntarily recruited and informed written consent was signed.In total, samples from 165 healthy individuals, 91 men and 74 women with mean age of 26.2 ± 3.2 years and 8 patients with type 1 diabetes aged between 20 and 36 years old were included in the study.The gender was self-reported by study participants.The participants had no signs of infection or inflammation on the day of blood collection.The experimental design is outlined in Supplementary Fig. S1.

MTT (3-(4,5-Dimethylthiazol-2-yl)-2, 5-Diphenyltetrazolium Bromide) assay
The metabolic activity of CD4 + T cells was assessed in 96-well plates with colorimetric MTT assay.It is commonly used to measure cellular metabolic activity based on mitochondrial dehydrogenase in living cells as an indicator of cell viability and proliferation. 21revious studies 10 and power analysis using R pwr-package was used to estimate sample size.After 66-72 h of activation, a PBS-soluble tetrazolium dye MTT (Cat.No. 5224/500, Tocris, UK; final concentration 1 mM) was added and incubated for additional 4 h at 37 • C. Thereafter, the cells were centrifuged at 2000 rpm for 10 min to concentrate the insoluble purple formazan pellets.The supernatants were collected and stored at −80 • C for later biomolecules analysis.The formazan crystal pellets were dissolved in DMSO and the plate was read 10 min later using Multiskan FC Microplate Photometer (Thermo Fisher, USA) at 540 nm.

Multiplex proximity extension assay (PEA)
The supernatants collected at the end of the MTT assay were sent on-ice to the SciLifeLab Affinity Proteomics Unit in Uppsala, Sweden, for analysis.Inflammatory proteins were measured using highthroughput multiplex PEA with an Olink Target 96 Inflammatory panel (Cat.No. 95302, OlinkProteomics, Uppsala, Sweden).PEA measures simultaneously 92 proteins/biomolecules in different sample matrices where it combines a dual-detection immunoassay and quantitative PCR.Normalised protein expression (NPX) values, an arbitrary unit on the log 2 scale, were used to present the data.A protein expression (NPX value) is considered acceptable if the value is above the limit of detection (LOD) for each particular protein.Proteins that were detected in more than 75% of the samples were analysed in this study: 59 or 53 out of 92 proteins had detectable levels, in samples from healthy individuals and patients with T1D, respectively.Data for resting, activated and GABA-treated activated CD4 + T cells supernatants were analysed separately.The biomolecules in the supernatants were assessed for each donor at each glucose concentration.The data were computed, processed and analysed with support from NBIS (National Bioinformatics Infrastructure Sweden).The log 2 FC (FC = fold change) is the average increase in NPX in GABA as compared to activated alone, this value is both estimated based on the linear mixed effects model and computed as the mean over the GABAactivated difference and plotted in heatmaps.Paired t-test was used followed by multiple testing correction using false discovery rate (FDR) method (Two-stage step-up method of Benjamini, Krieger and Yekutieli) with a threshold 12%.

Determination of IFNγ and IL-10 concentrations in supernatants
The concentrations of IFNγ and IL-10 were measured with enzyme-linked immunosorbent assay (ELISA).The supernatants were diluted when necessary to be in the optimal linear optical range and analysed using commercial kits for IFNγ (Human IFN-gamma DuoSet ELISA, Cat.No. DY285B, R&D Systems, USA and ELISA MAX™ Deluxe Set Human IFN-gamma, Cat.No. 430104, BioLegend, UK), and IL-10 (Cat.No. 430604, Biolegend, UK) according to manufacturers' instructions.Optical densities were measured using FC Microplate Photometer (Thermo Fisher, USA) at 450 nm, and 540 nm was used as a correction wavelength.The levels of IFNγ or IL-10 were normalised to controls (activated CD4 + T cells in the absence of drugs).

Total RNA and protein extraction
Total RNA and protein were extracted from activated CD4 + T cells, in the absence or presence of 500 nM GABA, using RNA/Protein Purification Plus Kit (Cat.No. 48200, Norgen Biotek, Ontario, Canada).During the extraction process, total RNA was treated with RNase-Free DNase I Kit (Cat.No. 25710, Norgen Biotek, Ontario, Canada) to eliminate contamination of genomic DNA.The extracted proteins were quantified using DC protein assay kit (Cat.No. 5000112, Bio-Rad, USA), and immediately frozen at −80 • C.

Real-time quantitative reverse transcription (qPCR)
The cDNA was synthesised using SuperScript reverse transcriptase IV (Cat.No. 18090010, Invitrogen, Thermo Scientific, USA) in a 20 μl reaction following the standard protocol from manufacturer.The qPCR reaction was then performed using qPCRBIO SYBR or Probe Mix low-ROX (Cat.No. PB20.11-05,PB20.21-05,PCR Biosystems, UK), and gene-specific primers (Supplementary Table S4) or Taqman probes (GABRR2 Hs00266703_m1; IPO8 Hs00914057_m1, Thermo-Fisher Scientific, USA).Changes in the abundance of each transcript were normalised to the expression of reference genes (IPO8).Relative expression levels were expressed as ΔCt (Ct, cycle threshold) or calculated by normalising to non-treated activated CD4 + T cells obtained from the same donor at the same glucose concentration using 2 -ΔΔCt method.All samples were run in duplicate.The real-time qPCR amplification was performed in 10 μl reaction mix in a 384-well plate using a QuantStudio™ 5 instrument (ThermoFisher Scientific).All runs started with an initial denaturation step of 2 min at 95 • C, followed by 45 cycles of 95 • C for 5 s and 60 • C for 30 s.

Mass spectrometry (MS)-based bottom-up proteomics
The lysates were purified and tryptic digested for MSbased bottom-up proteomic analysis using Filter Aided Sample Preparation (FASP). 22,23Briefly, 20 μg of total protein were transferred onto centrifugal filter units (Cat.No. MRCF0R030, Microcon-30 kDa; Merck, Darmstadt, Germany) and washed with a buffer containing 8 M urea and 100 mM Tris (pH 8.5).The washing step was repeated after reduction with 8 mM dithiothreitol (DTT), alkylation with 50 mM iodoacetamide (IAA) and removal excess of IAA with 8 mM DTT.Before tryptic digestion (enzyme-to-protein ratio 1:50 (w/w)) the filter was washed three times with NH 4 HCO 3 .After incubation in a wet chamber at 37 • C for 16 h the resulting peptides were washed twice from the filter by adding 50 mM NH 4 HCO 3 .Trifluoroacetic acid was then added to a final concentration of 1% (v/v) and the samples were dried at 45 • C. Finally, the samples were reconstituted in 3% acetonitrile and 0.1% formic acid in water to a final concentration of 150 ng protein/μl.The tryptic peptides were analysed on a nanoAcquity UPLC system equipped with a C18, 5 μm, 180 μm × 20 mm trap column and an HSS-T3 C18 1.8 μm, 75 μm × 250 mm analytical column (Waters Corporation, Manchester, UK) coupled to a Synapt G2 Si HDMS mass spectrometer with an electrospray ionisation source (Waters Corporation, Manchester, UK).The UDSME approach with positive ionisation was used. 22,23Mobile phase A contained 3% DMSO and 0.1% formic acid in water and mobile phase B 3% DMSO and 0.1% formic acid in acetonitrile.After loading 300 ng of protein on the column in trapping mode, peptide separation was performed with a gradient run from 3 to 40% (v/v) mobile phase B over 120 min.The flow rate was set to 0.3 μl/min and the column oven was set to 40 • C. Method performance was controlled with a commercially available HeLa digest (Cat.No. 88328, Thermo Scientific, Waltham, MA).UPLC-MS data processing and label-free quantification: ProteinLynx Global Server (version 3.0.3,Waters Corporation, Milford, MA) was used for raw data processing.With FDR of 10%, a database search against a randomised UniProt human database (Uni-ProtKB version 14/01/2020) was performed.Carbamidomethyl cysteine was set as fixed modification, acetyl lysine, C-terminal amidation, asparagine deamidation, glutamine deamidation and methionine oxidation as variable modifications and trypsin as digest reagent.Minimum peptide matches per protein were 2 and minimum fragment ion matches per peptide and protein were 1 and 3, respectively.For label-free quantification analysis, the identified proteins were further processed using ISOQuant 1.8 as described elsewhere. 22Following the TOP3 quantification approach the average intensity of the three most intense peptides of each protein were used for relative protein quantification.

In vitro hexokinase activity assay
Hexokinase activity was measured at RT indirectly as a readout of NADH production, a by-product of the reaction converting glucose-6-phosphate to 6-phosphogluconolacton by the enzyme glucose-6-phosphate dehydrogenase (GPDH).The cells were harvested, centrifugated and washed twice with PBS.Washed cells were resuspended in 1 ml assay buffer solution, on ice, included in the hexokinase enzymatic assay kit (Bio Vision, Cat.No. K789-100).After centrifugation at 4 • C for 5 min, the resulting supernatant was used as the final cell extract for the enzymatic assay.

Electrophysiological recordings
The electrophysiological recordings from the isolated CD4 + T cells were done using the perforated whole-cell patch-clamp configuration.In order to keep the intracellular chloride concentration intact, gramicidin was used to obtain the perforated configuration.Gramicidin (Cat.No. G5002, Sigma-Aldrich) was diluted in DMSO at the stock concentration 2 mg/ml and the final concentration of the gramicidin in the pipette solution was 2.6 μg/ml.The pipette solution with the gramicidin was protected from light, kept cold and used within 2 h after the preparation.After making the cell-attached configuration, the access resistance was monitored until characteristic slow and low-amplitude capacitance transients were observed and the access resistance decreased from GΩ range to the range of tens of MΩ.The extracellular solution (in mM) contained: 157 NaCl, 4.5 KCl, 0.5 CaCl 2 , 1 MgCl 2 , 5 HEPES and 5.6 or 16.7 glucose (pH 7.4, adjusted with NaOH).The pipette solution consisted of (mM): 149 KCl, 2 CaCl 2 , 1 MgCl 2 , 1 NaCl, 10 HEPES, 5.6 or 16.7 glucose (pH 7.3 adjusted with KOH).The single-channel recordings were done in the whole-cell patch-clamp configuration. 20The extracellular solution (in mM) contained: 137 NaCl, 3 KCl, 1 CsCl, 0.02 CaCl 2 , 2 MgCl 2 , 5 HEPES and 5.5 glucose (pH 7.4, adjusted with NaOH).The pipette solution consisted of (mM): 137 CsCl, 4 KCl, 0.01 CaCl 2 , 0.5 MgCl 2 , 5 HEPES, 5 EGTA, 2 Na 2 ATP (pH 7.3 adjusted with NaOH).The patch-clamp pipettes were made from borosilicate glass and had a resistance of 10-14 MΩ when filled with the pipette solution and immersed in the extracellular solution.Recordings were done using Axopatch 200B amplifier, filtered at 2 kHz and digitised on-line at 10 kHz using an analog-to-digital converter.To record the electrophysiological data Clampex 10.5 (Molecular Devices, San Jose, CA, USA) software was used.In the perforated patch-clamp configuration the currents were recorded at +30 mV or by a ramp protocol, where the potential was changed from −80 to +80 mV in 1 s, the holding potential (Vh) was kept −40 mV.The single sweep duration was 20 s with a break between sweeps 5 s.After application of a drug, the chamber was perfused 2-6 min with extracellular solution only, before next application of a drug.Currents in the absence of drugs or in the presence of picrotoxin were subtracted from the test-drug current response.For single-channel recordings, 20 currents were activated by perfusing 500 nM GABA into the recording chamber.The holding potential was changed in steps from −80 to +80 mV to record the current-voltage (IV) relationship of the channels.

Live cell time-lapse real-time Ca 2+ imaging
Cells were loaded with a calcium indicator, 3 μM Fluo-8 AM (Cat.No. 21082, AAT Bioquest, Pleasanton, CA) for 15 min at 37 • C and seeded on 5% 3aminopropyltriethoxysilane-coated coverslip (Cat.No. A3648, Sigma Aldrich) for 15 min at 37 • C. Time lapse images were acquired by confocal microscopy (LSM700, Zeiss) with 40X objective at an interval of 1-1.5 s per image.Drugs were diluted in RPMI 1640 without phenol red (Cat.No. 32404014, A2494201, Invitrogen) and perfused at indicated time and concentration by a peristaltic pump.After application of each drug, cells were perfused with the extracellular solution (RPMI 1640) before next application.Area for single cells was marked and absolute fluorescence intensity values (F) were extracted using ZEN software.Relative intensity (F/Fmedian) for each cell was calculated for every recorded image and plotted against time.Further, maximum relative intensity of the cells under drug application time is considered as drug's response.Data is represented for all cells and as box-whiskers plot.

Metabolism assay
Isolated CD4 + T cells were plated in a XFe96 cell plates that were coated with Cell-Tak (Cat.No. 354240, Corning, New York, USA) according to manufacturer's protocol.The metabolic function of activated CD4 + T cells cultured for 3 days in vitro was analysed by measuring the extracellular acidification rate (ECAR) using an XFe96 extracellular flux analyser (Seahorse Bioscience).The cells were kept in XF media (Seahorse Bioscience) supplemented with 5 mM glucose, and subjected to glycolysis stress-test protocol using sequential injection of 25 mM glucose, 2 μM oligomycin, and finally 15 mM 2-deoxyglucose (2DG).Measurements for each experiment were conducted at least in triplicate and glycolysis, glycolytic capacity, and glycolytic reserve were calculated and values normalised to protein content. 25,26

Statistics
Statistical analysis was performed using GraphPad Prism 9 (GraphPad Software Inc., La Jolla, CA, Version 9.3.1).Cellular metabolic activity, cytokine levels, mRNA, protein expression and ECAR of CD4 + T cells in the presence of indicated drugs were normalised to controls (activated cells without drug treatment) from each donor and for each glucose concentration.Shapiro-Wilk test was used to assess the data normality.Values more than 1.5 times the interquartile range (IQR) from the quartiles are defined as outliers (Tukey's methods) and presented outside whiskers in the boxand-whisker plot.For comparing two groups, paired ttest or Wilcoxon test for paired data, or Mann-Whitney test for unpaired data was performed.A comparison between multiple paired groups was performed using repeated measures one-way or two-way ANOVA or mixed-effects model followed by Tukey or Fisher's LSD multiple comparisons tests.Unpaired multiple-group comparison was performed using ordinary one-way ANOVA followed by Tukey test or Friedman test followed by Dunn's test.Changes in protein levels in MS data were analysed using Quantitative, multi-dataset Pathway Analysis (ReactomeGSA, https://reactome.org/PathwayBrowser/#TOOL=AT) and volcano plot was subsequently generated.Spearman correlation coefficients are annotated and linear regression line is plotted using "lm" package in R 4.0.0.The statistical significance level was set to 0.05.

Role of funders
The funders had no role in the study design, data collection, data analysis and interpretation, or the decision to prepare or publish this manuscript.

GABA inhibition of activated T cell function is affected by glucose
Physiological blood glucose concentration 2 h after a meal, is normally maintained around 5.6 mM in healthy individuals, while it is higher in diseases such as diabetes (>7 mM) 15 or Covid-19. 27The physiological GABA concentration in human plasma is about 500 nM 10,28 and provides a homeostatic inhibition on T cells. 10Importantly, metabolic activity of T cells is closely related to their function. 1Therefore, we examined effects of four glucose concentrations on the GABA inhibition of the metabolic activity of CD4 + T cells (N = 32-51 individuals; Fig. 1a; Supplementary Fig. S2a, Supplementary Table S1).At glucose concentrations higher (10 mM and 16.7 mM) than the typical physiological level (5.6 mM), the inhibition by GABA (500 nM) was abolished (Fig. 1a).In absence of GABA, the metabolic activity of activated CD4 + T cells varied somewhat for the different glucose concentrations.In the low-physiological glucose, 74% of the samples were inhibited by GABA (Supplementary Fig. S2b and c) whereas at the higher (10 mM and 16.7 mM) glucose concentrations, samples from these same individuals were not inhibited by GABA (Supplementary Fig. S2c).The remaining 26% of the samples that were obtained from different individuals were not inhibited by GABA at any glucose concentration (Supplementary Fig. S2d).Intrigued by these results, we sought to determine whether glucose affected other immunological functions regulated by GABA.Since glycolysis feeds substrates into anabolic metabolism, we studied if glucose modulated the GABA-inhibition of the release of biomolecules from CD4 + T cells cultured in low, physiological or high glucose.In each sample, 92 inflammatory-related biomolecules commonly associated with inflammation were measured using Olink Target Inflammation protein panel, which is based on the multiplex proximity extension assay (PEA) technology.A total of 59 different proteins were detected and included 23 pro-and 7 anti-inflammatory proteins identified by red and blue lettering (Fig. 1b), respectively.Similar to the results from the metabolic activity, the GABA-inhibition of proteins released from CD4 + T cells was glucose concentration-dependent (Fig. 1b).The GABA inhibition was optimal at the physiological glucose concentration (5.6 mM), where GABA decreased the release of 37 proteins, including 17 proand 3 anti-inflammatory proteins.In contrast, GABA did not affect release of proteins in either 10 mM nor 16.7 mM glucose (Fig. 1b).We further performed ELISA using CD4 + T cells culture supernatants from samples from healthy individuals, for two cytokines; interferon gamma (IFNγ), a pro-inflammatory and the principal cytokine of CD4 + T helper1 cells (Th1) and an anti-inflammatory protein interleukin-10 (IL-10), the principal cytokine for CD4 + T helper2 (Th2) and regulatory T (Treg) cells (Fig. 1c and d).GABA-mediated inhibition of IFNγ and IL-10 release was observed in low to physiological glucose (2.8 and 5.6 mM), but not in high glucose (10 and 16.7 mM) in samples from healthy individuals (Fig. 1c and d).In the absence of GABA, increasing the glucose concentration to 16.7 mM alone enhanced the release of IFNγ (Supplementary Fig. S2e) but not IL-10 in samples from healthy individuals (Supplementary Fig. S2f).In contrast, a total of 53 different proteins, including 21 pro-and 5 antiinflammatory proteins, were detected in the PEA assay in samples from patients with T1D (N = 8) but only 10 were significantly reduced by GABA (Fig. 2a), the majority at 5.6 mM glucose and included 5 pro-and one anti-inflammatory proteins.We further examined if correlation might be found between duration of diabetes or HbA1c levels in the samples from the patients with T1D and the proteins detected by PEA at each glucose concentration (Supplementary Fig. S3).For our relatively few samples, correlations are difficult to assess but, there is a trend for e.g., the levels of IFNγ and IL-10 at 5.6 mM glucose to correlate with diabetes duration and Hb1c that was not detected at the other glucose concentrations.We then examined by ELISA the culture supernatants from the CD4 + T cells from the patients with T1D (N = 7) (Fig. 2b and c).GABA significantly reduced the release of IFNγ and IL-10 from CD4 + T cells from the patients with T1D but only at the 5.6 mM glucose concentration (Fig. 2b and c).Thus, the results suggest that GABA-dependent regulation of CD4 + T cells is linked to the extracellular glucose concentration and is altered in T1D.

Insulin enhances the GABA-activated currents and modulates GABA A receptor expression in CD4 + T cells
Glucose homeostasis is influenced by a variety of hormones, with insulin being one of the key players.0][31] The insulin receptor is not expressed in resting T cells but is prominent at 48 h post-activation. 18Therefore, after 48 h activation, we incubated CD4 + T cells with insulin at physiologically relevant concentration (3 nM) and where unspecific activation of other receptors types does not take place. 18,31GABA activates two types of receptors in cell membranes; the GABA A receptor (GABA A R), a pentameric chloride ion channel, that opens when GABA binds to the receptor and the GABA B receptor (GABA B R), a G-protein coupled receptor, that is formed as a dimer.To date, only one of the two GABA B isoforms required for function has been detected in immune cells, whereas several GABA A receptor subunits are identified in T cells. 4 We measured the GABA-activated GABA A R wholecell currents in intact activated CD4 + cells using perforated patch-clamp electrophysiology (Fig. 3a, b,  c, e).GABA was acutely applied to the cells and the cells had not been exposed to GABA before.Since the intracellular environment is unchanged, the intracellular signalling that may take place is expected to function normally.The saturating, 500 nM GABAactivated GABA A R-mediated whole-cell currents were blocked by the GABA A R antagonist picrotoxin.
Picrotoxin is an open channel blocker of GABA A R.
These maximal whole-cell current responses were only enhanced by insulin at 5.6 mM but not at 16.7 mM glucose (Fig. 3a), whereas the apparent GABA affinity (EC 50 ) of GABA A R was similar in 5.6 mM and 16.7 mM glucose, 0.7 nM and 0.9 nM GABA, respectively (Fig. 3b).Insulin then shifted the EC 50 values more than 10-fold, to 0.04 nM and 0.06 nM GABA (Fig. 3c), for the two glucose concentrations, respectively.These results suggest that insulin may increase the GABA A R plasma membrane surface number in 5.6 mM glucose but enhances the GABA affinity of GABA A R in CD4 + T cells similarly at both glucose concentrations.The single-channel currents activated by 500 nM GABA showed outward rectification, and the channels were high-conductance at depolarised potentials (Fig. 3d), similar to hippocampal 32 GABA A R channels but the conductance was larger than reported for rat retinal 33 or expressed 34 ρ-containing GABA A R channels.The GABA A R agonists muscimol and TACA evoked whole-cell currents similar to GABA (Fig. 3e).The perforated-patch currents were stable (Supplementary Fig. S4b) and reversed at −37 mV (Supplementary Fig. S4a), close to the calculated reversal potential for chloride (E Cl = −39 mV).By regulating the membrane potential these very sensitive GABA A R channels may affect the activity of other ion channels or flow of ions across the cell membrane. 35mong the 19 GABA A R subunits, the GABA A R ρ2 (GABRR2) is a highly expressed subunit in peripheral blood mononuclear cells. 10We therefore examined the ρ2 mRNA and protein expression levels in CD4 + T cells.In 5.6 mM glucose, activation of CD4 + T cells decreased the expression of the GABRR2 transcript relative to resting cells, whereas insulin increased the expression again of the GABRR2 in the activated cells (Fig. 3f).In 16.7 mM glucose, the level of expression of GABRR2 was similar between activated and resting but insulin appeared to increase the level somewhat (Fig. 3f).Similar trend was observed for GABRR2 protein expression identified by ρ2-specific antibody in samples from homogenised CD4 + T cells (Fig. 3g) and where the GABRR2/ρ2 was detected by fluorescent labelling in the CD4 + T cells (Fig. 3h).Taken together, the data show that insulin potentiates GABA signalling in activated CD4 + T cells by enhancing ρ2-containing GABA A R expressed in the cells.

Insulin enhances GABA-activated Ca 2+ entry in CD4 + T cells
The cytoplasmic concentration of Ca 2+ ions is tightly regulated in T cells but can be increased by release from intracellular stores, or by entry through plasma membrane Ca 2+ ion channels. 36A representative live cell-Ca 2+ recording trace measured from activated CD4 + T cells (Fig. 4a) showed that acute GABA (500 nM) application induced a transient calcium signal, which was, in fact, influx of extracellular calcium and not due to release from intracellular stores as no signal could be detected in the absence of extracellular calcium (Fig. 4a).The cells had not been exposed to GABA before.Analysed live cell-Ca 2+ recording data from four donors is shown in Fig. 4b.What mechanisms the decay of the Ca 2+ signals is related to, remains to be studied.Transient, acute change in glucose from 5.5 to 16.7 mM did not alter the 500 nM GABA-activated Ca 2+ response (Supplementary Fig. S4c).Insulin incubation of cells enhanced the physiological, saturating (500 nM) GABAinduced Ca 2+ signals in 5.5 mM but not in 16.7 mM glucose (Fig. 4c), whereas no differences were observed for baseline Ca 2+ levels in cells with or without insulin incubation (Supplementary Fig. S4d).The GABAactivated Ca 2+ signal was blocked by the GABA A R antagonist picrotoxin (Fig. 4d), while no effect was observed by the GABA B R antagonist, CGP52432 (Supplementary Fig. S4e).This prompted us to examine the dose-response relationship between GABA and the Ca 2+ signals in cells with or without insulin incubation (Fig. 4e, f, g; Supplementary Fig. S4f and g).Representative time-lapse recording of a CD4 + T cell, 16.7 mM glucose, with insulin, demonstrates that raising GABA concentrations induced increasing Ca 2+ signals (Fig. 4e).Insulin incubation of the cells lowered the EC 50 values of the GABA-activated Ca 2+ signals.The apparent GABA affinity of the Ca 2+ signal was 40 nM and 156 nM GABA in 5.5 mM and in 16.7 mM glucose, and shifted more than 1000-fold to 0.005 nM and 0.14 nM GABA with insulin, respectively (Fig. 4f and g).At high GABA concentrations (≥10 μM), the Ca 2+ signal decreased which may be related to desensitisation of the GABA A R (Supplementary Fig. S4g).The GABA-induced Ca 2+ response and enhancement by insulin is in accordance with our electrophysiological patch-clamp calculated half maximal effective concentration (EC 50 ) in cells without (b) or treated with (c) insulin.The currents were normalised to 100 nM (b) or 100 pM (c), GABA responses (n = 3-11, N = 27).Curve fitting: nonlinear regression with sigmoidal polynomial (4 PL) model.d) Representative single-channel currents evoked by GABA (500 nM, +60 mV) in an activated CD4 + T cell.In symmetrical chloride solutions, the channels current-voltage relationship (lower left panel) is outwardly rectifying, and the channel conductance is greater at depolarised as compared to hyperpolarised potentials (lower right panel).e) Whole-cell currents (at +30 mV) evoked by GABA A R agonists GABA (n = 11, N = 9), muscimol (n = 4, N = 3) or TACA (n = 5, N = 4), in activated CD4 + T cells in 5.6 mM glucose.f) Relative expression of GABRR2 mRNA (ΔCt) in resting and activated cells in 5.6 mM or 16.7 mM glucose (N = 6).Box-whisker plots (black without and red with insulin: box as 25-75 percentiles, whiskers determined with Tukey's method, black lines in the boxes as median.g) Representative immunoblot images and relative expression of GABRR2 protein (N = 5).Target band volumes after total protein normalisation were further normalised to values of activated cells in the absence of GABA at each glucose concentration.h) Representative images from immunofluorescence co-staining of GABRR2 (green) and DAPI (blue) in CD4 + T cells in 5.6 mM or 16.7 mM glucose.Bar graphs show quantification of GABRR2 fluorescence intensity in CD4 + T cells (n ≥ 40 cells/group, N = 3).In experiments with insulin, 48-h post-activation insulin was added for 24-h.Data represent mean with 5-95 percentile in (a, e, g, h) and mean ± SD in (b, c, d).Statistics: ordinary (a, e, h) or repeated measures (f) one-way ANOVA followed by Tukey multiple comparison test; one sample t-test when compared to activated cell group (g).n: cells, N: donors.data (Fig. 3a, b, c).These data demonstrate that physiological GABA (pM-nM) increases Ca 2+ entry in activated CD4 + T cells, and the response is profoundly enhanced by insulin.
GABA A R agonists evoke Ca 2+ entry in CD4 + T cells To further confirm the GABA A R connection in the GABA-evoked Ca 2+ signal, we examined the pharmacological profile of the Ca 2+ response using GABA A R agonists and antagonists.The agonist TACA and the antagonist TPMPA are most selective for ρ-containing GABA A R. 37 In activated CD4 + T cells treated with or without insulin, the application of the GABA A R agonists muscimol (Fig. 5a), TACA (Fig. 5b) or GABA (Fig. 5a, b,  c) increased the relative Ca 2+ signals, which were then inhibited by the GABA A R antagonists picrotoxin (Fig. 5a, b, c) or TPMPA (Fig. 5c).Homomeric glycineactivated receptors can be inhibited by picrotoxin but not native heteromeric receptors. 38,39No effect of picrotoxin was detected on baseline recordings in the electrophysiological or Ca 2+ imaging experiments, in line with that to date active glycine receptors have not been identified in T cells. 38The pharmacological profile of the GABA A R is consistent with ρ-containing GABA A R being expressed and functional in the activated CD4 + T cells.But whether the receptors are homo-or heteromeric ρ2-containing GABA A R remains to be determined.
Ca 2+ release-activated Ca 2+ (CRAC) channels mediate store-operated calcium entry (SOCE) in T cells that is central to the Ca 2+ homeostasis and cytoplasmic Ca 2+ levels. 36The GABA-activated Ca 2+ signal was inhibited by 1 μM YM58483 (Fig. 5d), an antagonist of SOCE, revealing the Ca 2+ ion channel participating in the cascade.The tight scaling of the Ca 2+ signal from GABA A R activation to Ca 2+ entry and the sensitisation by insulin identifies a specific, focused mechanism regulating Ca 2+ signalling in CD4 + T cells.
Insulin is known to regulate intracellular signalling and gene expression, whereas less is known about the effects of GABA.However, out of the nine examined genes encoding transcription factors or kinases, only NFATC2 (nuclear factor of activated T cells 2, NFAT1) was significantly reduced by GABA at 5.6 mM glucose (Supplementary Table S2).At the protein level we observed a decrease with GABA for 10 mM but not for 5.6 mM glucose (Supplementary Fig. S5).Similar results were obtained for NFAT2 but no change was identified for NFAT4 (Supplementary Fig. S5).NFATs proteins are activated by increased Ca 2+ in the cytoplasm and translocate to the nucleus, where they impact T cell metabolism and regulate the transcription of many proteins including hexokinase and inflammatory molecules. 40

GABA regulation of glycolysis is glucose-dependent
That GABA regulated expression of the signalling pathways and proteins was revealed by mass spectrometry (MS) of activated CD4 + T cells cultured in the presence or absence of GABA (Fig. 6a, Supplementary Table S3).Hexokinase 1 (HK1), the first enzyme in the glycolytic pathway, was significantly down-regulated by GABA (Fig. 6a) and in both 5.6 mM and 16.7 mM glucose (Fig. 6b).HK activity was negligible under resting conditions but increased about 60 times in activated CD4 + T cells in both 5.6 mM and 16.7 mM glucose.GABA decreased the HK activity but only at 5.6 mM glucose and insulin had no further effect whereas in 16.7 mM glucose, in GABA and insulin, the HK1 activity increased somewhat (Fig. 6c).T cells switch to aerobic glycolysis upon activation as their predominant way to generate adenosine 5 ′ -triphosphate (ATP) and to accumulate biomass, 41,42 the so-called Warburg effect.It results in glucose-derived pyruvate being converted to lactate that can be detected by measuring the extracellular acidification rate (ECAR). 26ince HK is the gatekeeper for the glycolytic pathway, we examined if glucose, GABA or insulin modulated glycolysis.Representative ECAR traces and average values for activated CD4 + T cells at 5.6 mM and 16.7 mM glucose in the presence or absence of GABA and insulin are shown in Fig. 7a and b.GABA but not insulin inhibited glycolysis and glycolytic capacity but only in 5.6 mM glucose.Furthermore, the glycolysis and glycolytic capacity was reduced, in general, about 60% in 16.7 mM as compared to 5.6 mM glucose.No effect of GABA at 16.7 mM glucose might suggest the cells became exhausted or senescent in the high glucose concentration.Flow cytometry analysis of the T cells at 5.6 mM and 16.7 mM glucose revealed very low levels of exhaustion (Fig. 7c and d) and senescence, which were not affected by GABA or insulin treatment (Supplementary Fig. S6).The results are in agreement with a study reporting that hyperglycaemia hampers functionality of human CD8 + T cells. 43Our results raise time-lapsed micrographs of a live Ca 2+ imaged cell (16.7 mM glucose, with insulin).GABA concentrations (vertical bars on the left) were sequentially perfused (time indicated as min on the right) and inter-spaced with medium applications.Colour scale: Relative Ca 2+ fluorescence intensity.f, g) GABA dose-response relationship and the calculated half maximal effective GABA concentration (EC 50 ) for GABA-induced Ca 2+ signals in activated CD4 + T cells without or treated with insulin in 5.5 mM (f) or 16.7 mM (g) glucose (n = 63-279, N = 3-8), see also Supplementary Fig. S4f.Curve fitting: nonlinear regression with sigmoidal polynomial (3 PL) model.In (c, d), individual data point represents relative Ca 2+ signal recorded from each cell and is color-coded based on donors and box-whisker plots with Tukey's method.In experiments with insulin, 48-h post-activation insulin was added for 24 h.Statistics: Independent Mann-Whitney (c) or dependent Wilcoxon (d) test.n: cells, N: donors.
the possibility that high intracellular glucose levels negatively influence the GABA inhibition of glycolysis.

Discussion
T cells modulate their metabolism to adapt to different environments. 1,41,42When CD4 + T cells are activated, their metabolic activity is altered to meet the demands of cell growth, proliferation and effector functions.Here, we revealed that GABA, glucose and insulin together orchestrate functions of CD4 + T cells, to coordinate and to set the activity level of distinct cellular pathways linked to glucose metabolism and that are central for T cells effector functions (Fig. 8).
Proliferating T cells shift their metabolic phenotype to aerobic glycolysis at the expense of mitochondrial oxidative phosphorylation. 41,44Although this switch is inefficient in terms of generating ATP, it confers an advantage for the biosynthetic pathways that branch out from glycolysis. 41,42GABA decreased cellular metabolic activity and the release of proteins in a glucose concentration-dependent manner.GABA A Rs are widespread in the brain and are present in many other tissues, 45 but GABA A Rs containing GABRR (ρ subunits) are relatively rare outside the immune system, with the exception of the retina 46,47 and so far no pharmacological characterisation of native, human ρ2-containing GABA A R has been reported.The functional and pharmacological properties of GABA A R receptors are dictated by their subunit composition. 48The TACA activation and TPMPA inhibition of the receptors is consistent with ρ2-containing GABA A Rs but we do not know if the receptors in T cells are formed as homomeric ρ2 or ρ2 expressed with other GABA A R subunits. 47,49The GABA A R-ρ2 are abundantly expressed in the CD4 + T cells and are upregulated by insulin, suggesting they might be a valuable and rather specific drug target. 47,50Insulin shifted the GABA A R signalling by making it supersensitive to GABA, enhancing the GABA-switch, and consequently augmented the Ca 2+ entry through CRAC channels, an elegant way of modulating intracellular Ca 2+ levels and intracellular processes affecting T cell functions.
CRAC channel-mediated SOCE regulates several Ca 2+ signalling downstream pathways, including the expression of glucose transporters and glycolytic enzymes such as HK by activation of NFAT transcriptional factors in T cells. 40Our data show that GABA may decrease the expression of NFATs and the expression and enzymatic activity of HK at 5.6 mM glucose, in activated CD4 + T cells.Consequently, at the level of HK, there may be a cross-over of GABA signalling and glucose uptake for regulating glycolysis and, thereby, effector functions of T cells.HK is the first enzyme in the glycolytic pathway and by converting glucose to glucose-6-phosphate (G-6-P), traps glucose within the cell.Human HK has normally maximum activity in 5 mM glucose in the presence of natural inhibitors, such as G-6-P, 51 but HK activity is increased at glucose concentrations >5 mM. 51This is in line with our results, where GABA only succeeded decreasing HK enzymatic activity in 5.6 mM glucose.Glucose competes with G-6-P for the binding site on HK, 51 decreasing the inhibition of HK, 51 which results in increased substrate availability for biosynthesis as the intracellular glucose concentration increases. 14Aerobic glycolysis directly regulates synthesis of IFNγ 52 by engaging glyceraldehyde-3-phosphate dehydrogenase (GAPDH) and, thereby, relieving its inhibition of IFNγ mRNA translation.In concordance, activated CD4 + T cells secreted more IFNγ in high, atypical, glucose concentration.GABA induced a glycolytic shift reducing both glycolysis and the glycolytic capacity values in 5.6 mM glucose, which was absent in 16.7 mM glucose.Discovering that high glucose levels attenuate the immunosuppressive effect of GABA on CD4 + T cells, highlights the importance of metabolic factors in the context of GABA immunomodulation.Therefore, a combination treatment with glucose uptake inhibitors and GABA may synergistically dampen T cell functions.
The strength of the study is that it demonstrates how dynamic, environmental factors in the form of physiological molecules can shape the functional response of CD4 + T cells.Furthermore, we used human, primary CD4 + T cells to study the GABA signalling in immune cells.We and others have previously shown interspecies differences in the pentameric GABA A R subunit composition in T cells 49,53 and in pharmacology. 47or instance, ρ2 and γ2 subunits are only detected in human and mouse T cells, respectively, 49 and human ρ2-GABA A R receptors are much more sensitive to picrotoxin than the rat receptors. 47These species differences highlight the importance of using human cells to study functional and pharmacological characteristics of GABA signalling in T cells.
A limitation of our study is the number of samples from patients with T1D that were too few for carrying out detailed analysis of the cells.For the samples obtained from individuals that were healthy, we isolated CD4 + T cells from buffy coats prepared by the University hospital blood centre.The individuals that donated blood, self-reported to be healthy and were between 20 and 30 years old.However, other variables, including sex or undetected or unreported inflammation could potentially be confounding factors in this study.It will be critical to characterise further the GABA inhibition of Th1 respective to Th2 cells.So far it appears that GABA inhibits many more proinflammatory as compared to anti-inflammatory proteins but the specificities may be related to the microenvironment and other molecules present.It will be important to conduct further studies on the GABA-mediated inhibition of T cell functions in cells from individuals with either type 1 or type 2 diabetes where blood glucose concentrations may be increased above typical, physiological values.
In conclusion, physiological factors such as glucose, GABA, and insulin guide the adaptation of CD4 + T cells and modify their functions.The reduction of metabolic activity and the decreased release of inflammatory molecules in response to GABA, revealed a switch that can be turned on or off but a switch that is also modified by insulin and glucose.The study unveils the mechanisms of GABA modulation of CD4 + T cells.

Fig. 1 :
Fig. 1: GABA effects on metabolic activity and cytokine release are glucose concentration-dependent in activated CD4 + T cells.a) Violin plots show the cellular metabolic activity of activated CD4 + T cells as measured by MTT assay, in the absence and presence of GABA at different glucose concentrations: 2.8 (N = 32), 5.6 (N = 51), 10 (N = 32) and 16.7 mM (N = 51).Horizontal black and white lines indicate the median and quartiles, respectively.Grey circles indicate individual donors.Data were normalised to values of activated cells in the absence of GABA at 5.6 mM glucose concentration.b) Heatmap and hierarchical clustering of inflammatory-related proteins by PEA 72 h post-stimulation of CD4 + T cells, at different glucose concentrations (N = 17).Data represent the mean log 2 (fold change) for samples cultured in presence and compared to absence of GABA.c, d) Box plots show GABA inhibition of IFNγ (c) and IL-10 (d) release from CD4 + T cells from healthy individuals, as measured by ELISA, glucose concentrations (mM): 2.8 (N = 7; 7), 5.6 (N = 17; 17), 10 (N = 6; 10) and 16.7 (N = 16; 16) in c and d, respectively.Data were normalised to values of activated cells in the absence of GABA at each glucose concentration.Box and whisker: box as 25-75 percentiles, whiskers determined with Tukey's method, black lines in the boxes as median.Statistics: Repeated measures two-way ANOVA (mixed model) followed by Tukey for multiple comparisons (a), dependent t-test followed by multiple testing correction using false discovery rate (FDR) (b), Wilcoxon test for comparing paired raw values in the absence or presence of GABA at each glucose concentration, and mixedeffects analysis for normalised values among different glucose concentrations (c, d).P-values are indicated in the figures.N: donors.

Fig. 2 :Fig. 3 :
Fig. 2: GABA effects on cytokine release in activated CD4 + T cells from patients with type 1 diabetes (T1D).a) Heatmap and hierarchical clustering of inflammatory-related proteins by PEA 72 h post-stimulation of CD4 + T cells, at different glucose concentrations (N = 8).Data represent the mean log 2 (fold change) for samples cultured in presence and compared to absence of GABA.b, c) Box plots show GABA inhibition of IFNγ (b) and IL-10 (c) release from CD4 + T cells from patients with T1D, as measured by ELISA, glucose concentrations (mM): 2.8 (N = 5; 5), 5.6 (N = 7; 5), 10 (N = 7; 5) and 16.7 (N = 7; 4) in b and c, respectively.Data were normalised to values of activated cells in the absence of GABA at each glucose concentration.Box and whisker: box as 25-75 percentiles, whiskers determined with Tukey's method, black lines in the boxes as median.Statistics: Dependent t-test or Wilcoxon test for comparing paired raw values in the absence or presence of GABA at each glucose concentration (a, b, c), and mixed-effects analysis for normalised values among different glucose concentrations (b, c).P-values are indicated in the figures.N: donors.

Fig. 6 :
Fig.6: GABA inhibits hexokinase in activated CD4 + T cells.a) The volcano plot summarises pathways that are significantly regulated (blue dots including HK1 signalling) by GABA treatment in cells 72 h post activation (N = 5), 5.6 mM glucose.The x-axis represents the average foldchange of all proteins measured by mass spectrometry within that pathway and every dot is one pathway.The y-axis represents the adjusted P-value (-log10 transformation).The horizontal black and red line represents P = 0.05 and 0.01, respectively.b) Immunoblot images and relative expression of HK1 protein (N = 3-7).Target band volumes after total protein normalisation were further normalised to values of activated cells in the absence of GABA at each glucose concentration.Data are presented as mean with 5-95 percentile.c) In vitro HK activity analysed in resting and activated cells, 5.6 mM (N = 12) or 16.7 mM (N = 6) glucose.HK activity (μmol NADH/min/ml) was normalised to the activity of activated cells in the absence of drugs.Box-whisker plots (black without and red with insulin) display the whiskers using Tukey's method.In experiments with insulin, 48 h post-activation insulin was added for 24 h.Statistics: one sample t-test when compared to activated cell group, N: donors.

Fig. 7 :
Fig. 7: GABA inhibits glycolysis in activated CD4 + T cells.a) Representative ECAR over time in cells 72 h post-activation treated with or without GABA (500 nM) or insulin at 5.6 mM (left panel) or 16.7 mM (right panel).Dashed lines indicate injections into media of glucose (Glu.), oligomycin (Oligo) or 2-deoxyglucose (2-DG).Data represent mean ± SD. b) ECAR results (mpH/min/protein) were normalised to controls in absence of drugs for average glycolysis, glycolytic capacity and glycolytic reserve in cells 72 h post-activation treated with or without GABA or insulin, 5.6 mM (N = 5) or 16.7 mM (N = 5) glucose.Data are normalised to values of activated cells in the absence of drugs at each glucose concentration.c, d) Representative density plots (c) and quantification (d) showing the low percentage of PD-1 + CTLA4 + (exhausted) CD4 + T cells by flow cytometry.Box-whisker plots (black without and red with insulin) display the whiskers using Tukey's method (b, d).In experiments with insulin, 48-h post-activation insulin was added for 24-h.Statistics: one sample t-test when compared to activated cell group (b), Friedman test followed by Dunn's multiple comparisons test (d).N: donors.

Fig. 8 :
Fig. 8: GABA, glucose and insulin regulate CD4 + T cell functions.In human CD4 + T cells, the activation of the T cell receptor (TCR)/CD3 complex by anti-CD3 antibodies binding, initiates store-operated Ca 2+ entry (SOCE) through Ca 2+ release-activated Ca 2+ (CRAC) channels.It regulates intracellular Ca 2+ signals, drives changes in transcription factors, upregulates glycolysis and increases T cell effector functions.Physiological concentration of GABA (pM-nM) activates GABA A R to modulate T cells metabolic activity and levels of released cytokines (e.g., IFNγ and IL-10) by 1) enhancing function of CRAC channels and Ca 2+ entry; 2) reducing expression of Nuclear Factor of Activated T cell (NFAT); 3) decreasing expression and activity of hexokinase (HK), the 1st rate-limiting enzyme in aerobic glycolysis.In addition, insulin-insulin receptor (IR) signalling reduces glycolysis by enhancing GABA A R function.The fluctuation of blood glucose concentration will affect glycolysis and cytokine release from T cells.Created with BioRender.com.